Fig 2. Linear readout and its interpretation.

(A) We study a “standard” model of percept formation, with two parameters w and t _R defining integration in time, and a readout vector a defining integration across neurons. (B) Geometric interpretation of the model. The temporal parameters w and t _R define the tuning vector $\overline{\mathbf{\text{b}}}$ and noise covariance matrix $\stackrel{‾}{\overline{\mathbf{\text{C}}}}$ in the population. Colored ellipses represent the distribution of neural activities from trial to trial, for the three possible stimulus values. The readout $\hat{s}$ can be viewed as an orthogonal projection of neural activities in the direction given by a. (C) Behavioral part of the model. The percept $\hat{s}$ can be corrupted by decision noise ξ _d. Then it is thresholded to produce a binary choice c.